NeurIPS 2020poster19 citations
Truncated Linear Regression in High Dimensions
Constantinos Daskalakis, Dhruv Rohatgi, Emmanouil Zampetakis
Abstract
As in standard linear regression, in truncated linear regression, we are given access to observations (A
BibTeX
@inproceedings{NEURIPS2020_751f6b6b,
author = {Daskalakis, Constantinos and Rohatgi, Dhruv and Zampetakis, Emmanouil},
booktitle = {Advances in Neural Information Processing Systems},
editor = {H. Larochelle and M. Ranzato and R. Hadsell and M.F. Balcan and H. Lin},
pages = {10338--10347},
publisher = {Curran Associates, Inc.},
title = {Truncated Linear Regression in High Dimensions},
url = {https://proceedings.neurips.cc/paper_files/paper/2020/file/751f6b6b02bf39c41025f3bcfd9948ad-Paper.pdf},
volume = {33},
year = {2020}
}